Abstract

This study investigates the physical mechanisms that contributed to the 2016 Eurasian heat wave during boreal summer season (July–August, JA), characterized by much higher than normal temperatures over eastern Europe, East Asia, and the Kamchatka Peninsula. It is found that the 2016 JA mean surface air temperature, upper-tropospheric height, and soil moisture anomalies are characterized by a tri-pole pattern over the Eurasia continent and a wave train-like structure not dissimilar to recent (1980–2016) trends in those quantities. A series of forecast experiments designed to isolate the impacts of the land, ocean, and sea ice conditions on the development of the heat wave is carried out with the Global Seasonal Forecast System version 5. The results suggest that the tri-pole blocking pattern over Eurasia, which appears to be instrumental in the development of the 2016 summer heat wave, can be viewed as an expression of the recent trends, amplified by record-breaking oceanic warming and internal land-atmosphere interactions.

Highlights

  • The unusually severe heat wave events that have occurred around the world in recent decades have had a profound negative impact on human health, ecosystems, and socioeconomies (WMO 2011, Coumou and Rahmstorf 2012)

  • This study investigates the physical mechanisms that contributed to the 2016 Eurasian heat wave during boreal summer season (July–August, JA), characterized by much higher than normal temperatures over eastern Europe, East Asia, and the Kamchatka Peninsula

  • When the leading SST pattern of global warming is prescribed in five atmospheric general circulation models (AGCMs) (Schubert et al 2009), the resulting JAmean surface temperature response (supplementary figure 2(a)) is similar in structure to the recent warming trend over Eurasia, especially with significant warming signals in eastern Europe and East Asia

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Summary

16 October 2020

Eunkyo Seo1,5 , Myong-In Lee, Siegfried D Schubert, Randal D Koster and Hyun-Suk Kang.

Introduction
Observational data
LSM offline simulation This study first integrated the stand-alone LSM model in
Experiment design This study used the UK Met
Heat wave days and intensity
Model hindcasts of the 2016 Eurasian heat wave
Conclusions
Full Text
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